Bayesian Filtering and Smoothing

ISBN-13: 9781108926645 / Angielski

Simo S?rkk?; Lennart Svensson

Opis

The second edition of this accessible introduction for graduate students and advanced undergraduates presents the current state-of-the-art filtering and smoothing methods in a unified Bayesian framework. The book introduces all the main concepts and ideas, and contains numerous examples and exercises to let you put the theory into practice.

Recenzje

'An excellent and pedagogical treatment of the complex world of nonlinear filtering.  It is very valuable for both researchers and practitioners.' Lennart Ljung, Linköping University

Spis treści

Symbols and abbreviations; 1. What are Bayesian filtering and smoothing?; 2. Bayesian inference; 3. Batch and recursive Bayesian estimation; 4. Discretization of continuous-time dynamic models; 5. Modeling with state space models; 6. Bayesian filtering equations and exact solutions; 7. Extended Kalman filtering; 8. General Gaussian filtering; 9. Gaussian filtering by enabling approximations; 10. Posterior linearization filtering; 11. Particle filtering; 12. Bayesian smoothing equations and exact solutions; 13. Extended Rauch-Tung-Striebel smoothing; 14. General Gaussian smoothing; 15. Particle smoothing; 16. Parameter estimation; 17. Epilogue; Appendix. Additional material; References; Index.